The city-wide deployment of IoT technologies brings the need to process large amounts of sensor data, some of it in real time. The InterSCity project is developing ContextNet, which aims at implementing a middleware for large-scale, low-latency processing of mobile data streams with support for mobile-mobile cooperation, context awareness, connection balancing, and cloud integration.
Being able to simulate the execution of Smart Cities scenarios would be extremely beneficial for the advancement of the field. The InterSCity project is buinding an open-source, extensible, large-scale Traffic Simulator for Smart Cities developed in Erlang, capable of simulating millions of agents using a real map of a large city. Future versions will be extended to address other Smart City domains.
Despite the various advances in middleware technologies to support future smart cities, there are no universally accepted platforms yet. The InterSCity project is developing a microservice-based, open-source smart city platform that aims at supporting collaborative, novel smart city research, development, and deployment initiatives. The microservice approach enables a flexible, extensible, and loosely coupled architecture.